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Edge AI: Revolutionizing Embedded Systems through On-Device Processing

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  • Anushree Nagvekar

Abstract

This comprehensive article explores the transformative impact of edge AI computing on embedded systems, highlighting the paradigm shift from cloud-dependent to on-device processing. The article examines the architectural foundations, performance benefits, security advantages, and implementation considerations of edge AI systems. The article demonstrates how edge computing addresses critical challenges in latency, cost efficiency, data privacy, and operational reliability across various applications, particularly in autonomous systems. The article encompasses detailed analyses of hardware accelerators, memory architectures, power management strategies, and security frameworks, providing insights into both current capabilities and future developments. By examining real-world deployments across multiple sectors, the article illustrates how edge AI technology is revolutionizing embedded systems through improved processing efficiency, reduced operational costs, enhanced security measures, and optimized resource utilization.

Suggested Citation

  • Anushree Nagvekar, 2025. "Edge AI: Revolutionizing Embedded Systems through On-Device Processing," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(1), pages 2871-2880, February.
    • Handle: RePEc:jbh:ijsrcs:v11:y2025:i1:id:958
    DOI: 10.32628/CSEIT251112289
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT251112289
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